**GROUP BY Syntax:**

```sql

SELECT

grouping_columns,

aggregate_functions

FROM table

WHERE conditions

GROUP BY grouping_columns

HAVING aggregate_conditions

ORDER BY columns;

```

**PARTITION BY Syntax:**

```sql

SELECT

all_columns,

window_function() OVER (PARTITION BY columns)

FROM table

WHERE conditions

ORDER BY columns;

```

**Combined Syntax:**

```sql

WITH grouped_data AS (

SELECT col1, AGG(col2) as summary

FROM table GROUP BY col1

)

SELECT

original.*,

FUNC() OVER (PARTITION BY col1) as context,

grouped_data.summary

FROM table original

JOIN grouped_data ON original.col1 = grouped_data.col1;

```

GROUP BY collapses rows into groups - one row per unique combination of grouping columns

PARTITION BY preserves all rows while adding group-level calculations as new columns

GROUP BY requires aggregate functions (COUNT, SUM, AVG) in SELECT clause

PARTITION BY uses window functions with OVER clause for calculations

Both can be combined in the same query using CTEs or subqueries

HAVING clause filters groups in GROUP BY, WHERE clause filters individual rows

Excellent support for both approaches. Advanced window functions and parallel GROUP BY processing.